Analysis and modelling of profiles to understand fractionation processes for contaminations with polychlorinated biphenyls observed in fish.

Polychlorinated biphenyls (PCB) both continue to spread into the environment and to bioaccumulate from primary urban and industrial sources as well as from secondary sources such as soils and the oceans. Fractions of congeners in PCB mixtures, i.e. PCB profiles, can be used as fingerprints to trace contamination pathways from sources to sinks because PCB mixtures fractionate during transport due to congener specific phase changes and degradation. Using a statistical analysis of a total of 8584 PCB profiles with seven congeners (CB28, CB52, CB101, CB118, CB138, CB153, CB180) for contaminated fish from two international datasets as well as a modelling of profiles, two major fractionation processes related to distinct contamination pathways were identified: (1) A relative enrichment of lighter congeners (CB28, CB52, CB101) in seawater fish due to a predominantly atmospheric transport, whereas freshwater and some coastal fish had higher fractions of heavier congeners (CB138, CB153) because those were mainly contaminated by particle-sorbed PCB from surface runoff. (2) A temperature driven fractionation tended to affect congeners with a medium molecular weight (CB118) as well as the heaviest congeners (CB180), a fractionation process which was conceptually associated with transport of PCB from secondary sources. Specifically, medium chlorinated PCB is sufficiently volatile and persistent for a preferred transport into cooler waters. In warmer climates, only the highest chlorinated congeners are persistent enough to ultimately accumulate in fish. Our analysis and modelling provide a starting point for the development of systems to trace - better than before - sources of PCB contaminations observed in fish.

LogD-based modelling and ΔlogD as a proxy for pH-dependent action of ionizable chemicals reveal the relevance of both neutral and ionic species for fish embryotoxicity and possess great potential for practical application in the regulation of chemicals.

Depending on the ambient pH, ionizable substances are present in varying proportions in their neutral or charged form. The extent to which these two chemical species contribute to the pH-dependant toxicity of ionizable chemicals and whether intracellular ion trapping has a decisive influence in this context is controversially discussed. Against this background, we determined the acute toxicity of 24 ionizable substances at up to 4 different pH values on the embryonic development of the zebrafish, Danio rerio, and supplemented this dataset with additional data from the literature. The LC50 for some substances (diclofenac, propranolol, fluoxetine) differed by a factor of even >103 between pH5 and pH9. To simulate the toxicity of 12 acids and 12 bases, six models to calculate a pH-dependant logD value as a proxy for the uptake of potentially toxic molecules were created based on different premises for the trans-membrane passage and toxic action of neutral and ionic species, and their abilities to explain the real LC50 data set were assessed. Using this approach, we were able to show that both neutral and charged species are almost certainly taken up into cells according to their logD-based distribution, and that both species exert toxicity. Since two of the models that assume all intracellular molecules to be neutral overestimated the real toxicity, it must be concluded, that the toxic effect of a single charged intracellularly present molecule is, on the average, lower than that of a single neutral molecule. Furthermore, it was possible to attribute differences in toxicity at different pH values for these 24 ionizable substances to the respective deltas in logD at these pH levels with high accuracy, enabling particularly a full logD-based model on the basis of logPow as a membrane passage descriptor to be used for predicting potential toxicities in worst-case scenarios from existing experimental studies, as stipulated in the process of registration of chemicals and the definition of Environmental Quality Standards (EQS).

An assessment of mercury and its dietary drivers in fur of Arctic wolves from Greenland and High Arctic Canada.

Mercury has become a ubiquitous hazardous element even ending up in pristine areas such as the Arctic, where it biomagnifies and leaves especially top predators vulnerable to potential health effects. Here we investigate total mercury (THg) concentrations and dietary proxies for trophic position and habitat foraging (δ15N and δ13C, respectively) in fur of 30 Arctic wolves collected during 1869-1998 in the Canadian High Arctic and Greenland. Fur THg concentrations (mean ± SD) of 1.46 ± 1.39 µg g -1 dry weight are within the range of earlier reported values for other Arctic terrestrial species. Based on putative thresholds for Hg-mediated toxic health effects, the studied Arctic wolves have most likely not been at compromised health. Dietary proxies show high dietary plasticity among Arctic wolves deriving nutrition from both marine and terrestrial food sources at various trophic positions. Variability in THg concentrations seem to be related to the wolves' trophic position rather than to different carbon sources or regional differences (East Greenland, the Foxe Basin and Baffin Bay area, respectively). Although the present study remains limited due to the scarce, yet unique historic study material and small sample size, it provides novel information on temporal and spatial variation in Hg pollution of remote Arctic species.

Heart rate as an early warning parameter and proxy for subsequent mortality in Danio rerio embryos exposed to ionisable substances.

Environmental risk assessments of organic chemicals usually do not consider pH as a key factor. Hence, most substances are tested at a single pH only, which may underestimate the toxicity of ionisable substances with a pKa in the range of 4-10. Thus, the ability to consider the pH-dependent toxicity would be crucial for a more realistic assessment. Moreover, there is a tendency in acute toxicity tests to focus on mortality only, while little attention is paid to sublethal endpoints. We used Danio rerio embryos exposed to ten ionisable substances (the acids diclofenac, ibuprofen, naproxen and triclosan and the bases citalopram, fluoxetine, metoprolol, propranolol, tramadol and tetracaine) at four external pH levels, investigating the endpoints mortality (LC50) and heart rate (EC20). Dose-response curves were fitted with an ensemble-model to determine the true uncertainty and variation around the mean endpoints. The ensemble considers eight (heart rate) or twelve (mortality) individual models for binominal and Poisson distributed data, respectively, selected based on the Akaike Information Criterion (AIC). In case of equally good models, the mean endpoint of all models in the ensemble was calculated, resulting in more robust ECx estimates with lower 'standard errors' as compared to randomly selected individual models. We detected a high correlation between mortality (LC50) at 96 hpf and reduced heart rate (EC20) at 48 hpf for all compounds and all external pH levels (r = 0.98). Moreover, the observed pH-dependent effects were strongly associated with log D and thus, likely driven by differences in uptake (toxicokinetic) rather than internal (toxicodynamic) processes. Prospectively, the a priori consideration of pH-dependent effects of ionisable substances might make testing at different pH levels redundant, while the endpoint of mortality might even be replaced by a reliable sublethal proxy that would reduce the exposure, accelerating the evaluation process.

Better define beta-optimizing MDD (minimum detectable difference) when interpreting treatment-related effects of pesticides in semi-field and field studies.

The minimum detectable difference (MDD) is a measure of the difference between the means of a treatment and the control that must exist to detect a statistically significant effect. It is a measure at a defined level of probability and a given variability of the data. It provides an indication for the robustness of statistically derived effect thresholds such as the lowest observed effect concentration (LOEC) and the no observed effect concentration (NOEC) when interpreting treatment-related effects on a population exposed to chemicals in semi-field studies (e.g., micro-/mesocosm studies) or field studies. MDD has been proposed in the guidance on tiered risk assessment for plant protection products in edge of field surface waters (EFSA Journal 11(7):3290, 2013), in order to better estimate the robustness of endpoints from such studies for taking regulatory decisions. However, the MDD calculation method as suggested in this framework does not clearly specify the power which is represented by the beta-value (i.e., the level of probability of type II error). This has implications for the interpretation of experimental results, i.e., the derivation of robust effect values and their use in risk assessment of PPPs. In this paper, different methods of MDD calculations are investigated, with an emphasis on their pre-defined levels of type II error-probability. Furthermore, a modification is suggested for an optimal use of the MDD, which ensures a high degree of certainty for decision-makers.